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MESABI IRON RANGE WATER AND MINERAL RESOURCE PLANNING

STOCKPILE OWNERSHIP, COMPOSITION, AND USEFOR TWO STUDY AREAS LOCATED NEAR VIRGINIA AND CALUMET, MINNESOTA

BY THE MINNESOTA DEPARTMENT OF NATURAL RESOURCES

DIVISION OF LANDS AND MINERALS

PROJECT: 350

JUNE 2001

TABLE OF CONTENTS

EXECUTIVE SUMMARY............................................................................................................... iI. INTRODUCTION..................................................................................................................... 1II. SCOPE................................................................................................................................... 2III. METHODOLOGY................................................................................................................... 4

A. OWNERSHIP............................................................................................................... 4Surface and Mineral OwnershipStockpile Ownership

B. STOCKPILE MATERIAL INVENTORY........................................................................... 6Stockpile Composition

Company InformationField WorkAerial Photographic InterpretationMining Maps

Stockpile Material ClassificationAggregate TestingIron Ore TestingStockpile DigitizingVolume Estimation

C. DATABASE DESIGN................................................................................................... 14D. STOCKPILE ACCESS................................................................................................... 15

VegetationTransportation

IV. RESULTS.............................................................................................................................. 16A. OWNERSHIP................................................................................................................ 16

Surface and Mineral OwnershipStockpile Ownership

B. STOCKPILE MATERIAL INVENTORY........................................................................... 19Stockpile Material DescriptionsAggregate Testing ResultsMaterial OverviewIron Ore Results

C. DATABASE RESULTS................................................................................................. 34D. STOCKPILE ACCESS................................................................................................... 34

VegetationTransportation

V. STOCKPILE USES.................................................................................................................. 35

REFERENCES................................................................................................................................ 39Appendices

Plate I: Ownership, Calumet Study AreaPlate II: Ownership, Virginia Study AreaPlate III: Material Type, Vegetation, and Transportation, Calumet Study AreaPlate IV: Material Type, Vegetation, and Transportation, Virginia Study AreaCD-ROM

LIST OF FIGURES AND TABLES

FIGURES:

Figure 1. Location of the two study areasFigure 2. Virginia and Calumet study areasFigure 3. Description of section, government lot, and townshipFigure 4. Schematic diagram of stockpile classification systemFigure 5. Picture of glacial tillFigure 6. Picture of slateFigure 7. Picture of coarse tailingsFigure 8. Specific gravity by material typeFigure 9. Absorption by material typeFigure 10. Soundness resultsFigure 11. Examples of gradation results

TABLES:

Table 1. Sample list by material typeTable 2. Tests performed on each sampled material typeTable 3. Glacial overburden test resultsTable 4. Glacial overburden test resultsTable 5. Cretaceous ore test resultsTable 6. Cretaceous ore test resultsTable 7. Natural ore coarse tailings test resultsTable 8. Natural ore coarse tailings test resultsTable 9. Natural ore fine tailings test resultsTable 10. Natural ore fine tailings test resultsTable 11. Mixed-sized rock test resultsTable 12. Mixed-sized rock test results

ACKNOWLEDGMENTS

The Department of Natural Resources, Division of Lands and Minerals acknowledgesfunding for this project from the Minnesota Legislature, ML 1999, Chapter 231, Section 16,Subdivision 7(k) as recommended by the Legislative Commission on Minnesota Resources. Wefurther recognize the cooperation of U.S. Steel Group - Northern Lands and Minerals, GreatNorthern Iron Ore Properties, Gardner Management Services, and Consolidated Title andAbstract Company, Duluth, Minnesota.

This project was completed by the following Department of Natural Resources, Division ofLands and Minerals staff:

Vicki Hubred - Ownership ResearchHeather Anderson - Stockpile InventoryJim Sellner - Composition ResearchSteve Dewar - Vegetation InventoryJill Bornes - Database DesignRenee Johnson - GIS Design and Plates Layout

EXECUTIVE SUMMARY

This report summarizes the results of a data collection project focused on stockpile ownership,material composition, and material use for two study areas located near Virginia and Calumet,Minnesota. The information collected may be used to determine the suitability of stockpilematerials for future use. Funding for the project was from the Legislative Commission onMinnesota Resources. The project was conducted by the Minnesota Department of NaturalResources, Division of Lands and Minerals.

Surface and mineral ownership research was completed for 2,839.32 acres in the Virginia studyarea. A total of 4,067.02 acres were researched in the Calumet study area, with an additional2,498.99 acres, which were previously researched, checked for ownership changes. Stockpileownership was determined for a majority of the stockpiles located within the study areas,however, many stockpiles still have undetermined ownership.

A total of 232 stockpiles were inventoried in the two study areas. The stockpile inventoryinvolved gathering information regarding material composition, material classification, sampleanalysis, and volume estimation. Material was classified into ten material types based upongeology and iron content. The footprint of each stockpile was digitized to capture the location ofthe stockpile.

Eighty-two samples were collected from stockpiles. The samples were tested for aggregate andiron ore. Aggregate tests included: specific gravity, absorption, soundness, and gradations. Thetest results were compared to the Minnesota Department of Transportation specifications forgeneral aggregate use. Iron ore testing was comprised of chemical assays of the eight mostcommon oxides.

A relational database was designed to store the information gathered for this project. This is thefirst known attempt to model and develop a database which would accommodate thecomplexities of stockpiles and ownership on the Mesabi Iron Range. The database consists ofover 30 related tables and forms for browsing the information.

Vegetation covers on the stockpiles were determined through aerial photography interpretationand field checked during the fall of 2000. The current transportation infrastructure, whichincludes major roads and railroads, and private mining roads and old railroads, was mappedduring the summer of 2000.

The stockpiles were examined for use in the aggregate industry and the iron mining industry. Generalizations can be made about each material type based upon qualitative and quantitativedata. The material type with the highest potential for aggregate use was glacial overburden. Cretaceous ore and natural ore fine tailings have a high potential for iron.

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VirginiaCalumet

Figure 1. Location map of the two study areas nearthe towns of Virginia and Calumet, Minnesota.

I. INTRODUCTIONOver 100 years of mining on the Mesabi Iron Range has resulted in large scale land disruptions. Large, deep water bodies, mounds of stockpiled materials, and vast plains of tailings make up thelandscape of the Mesabi Iron Range. The Mesabi Iron Range Water and Mineral ResourcesPlanning project initiates the effort to provide the people of the Range with technical data that willassist them in planning and developing this landscape.

This portion of the Legislative Commission on Minnesota Resources (LCMR) project focuses onStockpile Ownership, Composition, and Use. The project’s purpose is to collect data on stockpileownership and material composition within two study areas. The data may be used to determine thesuitability of stockpile materials for future uses. The large volume of stockpiled material on theMesabi Iron Range has great potential for re-use. Certain materials have the potential to be used asaggregate, while some materials have the potential to be mined for iron units with the developmentof new processing techniques. Helping to sustain the mining industry and local communities byutilizing stockpiles requires the development of information on stockpile ownership andcomposition.

This is a first attempt to join and reconcile the complexity of ownership data on mining propertieswith data defining and categorizing stockpile material types. Because each data set has distinctgeographic boundaries, the difficulty in combining them is compounded. Disparate data sets neededto be gathered, organized, linked, and then stored. To accomplish these tasks the project was brokendown into five parts:

• Ownership Research• Stockpile Inventory• Database Design• Stockpile Access• Potential Material Use

Ownership involved title research to determinethe mineral, surface, and stockpile ownership. The stockpile inventory was based upon pre-existing information gathered from various miningcompanies and field work. For the purposes ofthis project, a “stockpile” is defined as anyearthen material piled during the process ofmining. This includes tailing basins, overburdenpiles, and rock dumps. If the material had anotherintended use, such as material used for a dike,overpass, or road base, that material is not considered to be a stockpile for purposes of this project. The various aspects of ownership research and the stockpile inventory were organized and linked ina database designed in Microsoft Access. To further facilitate the use of stockpiled material,accessibility was examined by mapping vegetation and mining roads. The potential use of stockpileswas summarized by past leasing experience and through sampling analysis of different types ofstockpiled material.

The project was conducted over two study areas on the Mesabi Iron Range (Figure 1). One site islocated on the east end of the Mesabi Iron Range, east of the city of Virginia, in St. Louis

County, comprising approximately 3,000 acres (hereafter referred to as the “Virginia” site). TheVirginia site encompasses portions of Township 58 North, Range 17 West. The second site islocated on the west end of the Mesabi Iron Range, in the vicinity of the cities of Calumet andMarble, in Itasca County, comprising approximately 6,000 acres (hereafter referred to as the“Calumet” site). The Calumet site encompasses portions of Township 56 North, Range 23 Westand Township 56 North, Range 24 West (Figure 2).

The study areas were selected based upon the following site criteria: 1) numerous stockpileswithin the area with a variety of potential materials; 2) area with known state surface ownership;3) inactive iron ore/taconite mining area; and 4) proximity to transportation. An east Range siteand a west Range site were selected to show differences that may be encountered in differentmining areas along the Range. In the interest of project manageability, the two combined studyareas were not to contain more than a total of 10,000 acres. The boundaries of the study areaswere determined using plat maps, preliminary site visits, and personal knowledge of the stockpileareas by the Minnesota Department of Natural Resources (DNR), Division of Lands andMinerals staff. The boundaries were drawn following public land survey lines along forty-acreparcels or government lots. Some stockpiles within the study areas may extend beyond theseboundary lines.

II. SCOPEThroughout this project, DNR, Division of Lands and Minerals staff have made a best effort tocollect accurate data using available sources. Because this project is geared towards aggregateand iron ore potential, the method by which this information was organized and mapped wascustomized for that purpose. The methodology used could be expanded Range-wide, however,modifications would be needed in the database and in stockpile classification. The databasestructure designed for this project may or may not work for other stockpile inventories andownership research. It is also important to note that the designed database is the first attempt togather and store many pieces of stockpile information in one place.

Information gathered from private companies is based upon the best information available at thetime the information was collected. Every company has its own method of collecting data andfield checks were not always conducted. Therefore, the accuracy of the data cannot be reliedupon without conducting a closer examination of stockpiled materials.

The information gathered from the two study areas occurred between 1999 and 2001. Theproject only provides a “snapshot in time” for the areas. This is especially true regarding thesurface, mineral and stockpile ownership. Due to ownership changes which occur whenever aconveyance of property is made, ownership is only accurate as of the day the ownership wasreviewed. Currently, there is no plan to update the stockpile information database to reflectchanges which may occur in the two study areas after June 30, 2001.

III. METHODOLOGYA. OWNERSHIP

Surface and Mineral OwnershipThe surface and mineral ownership were determined based upon a review of the documentscomprising the chain of title for each forty-acre parcel or government lot within the study areas. Only those documents recorded in the Itasca County Recorder’s Office and the St. Louis CountyRecorder’s Office, which were indexed against the specific parcels in each study area, werereviewed.

Ownership research for the Virginia study area was conducted in St. Louis County from August1999 through January 2000. Due to the absence of a complete tract index (an index of recordeddocuments by legal description) in the St. Louis County Recorder’s Office, assistance wasprovided by Consolidated Abstract and Title Company in Duluth, Minnesota in locatingdocuments recorded in the county’s records. Ownership research for the Calumet study area wasconducted in Itasca County from June 2000 through January 2001.

Ownership is broken down to the forty-acre parcel or government lot (Figure 3). (Governmentlots numbers were generally assigned to those parcels which have more or less than the standardforty acres, or parcels adjoining meandered waters). Some parcels contain partial descriptions fordiffering ownership within the parcel. Multiple owners with undivided, fractional interests in aparcel are common for parcels throughout the two study areas. Parcels that have been platted aslots and blocks were not researched, due to their small acreage and often complicated ownership. Since property ownership changes over time with conveyances of the property, the ownershipresults are only valid as of the date the research was conducted in the county.

In areas where there has been mining activity, it is common for parcels to have separate surfaceand mineral ownership. The surface estate and mineral estate are considered one entity until atransaction separates them, creating a “severance” of the mineral estate. Where the mineralshave been severed, the surface owner and the mineral owner will differ. The owner of severedminerals must file a statement of such ownership with the county recorder in the county wherethe minerals are located. The owner is then assessed taxes on this mineral ownership. Failure tofile the statement or pay the taxes results in the forfeiture of the mineral rights.

A short explanation is needed regarding State ownership of the surface and minerals. The Statemay own real estate acquired through different methods. State trust fund lands are lands ownedby the State through a direct conveyance from the United States government. The State may alsoacquire land from a private owner by purchase or gift, or through an exchange of State land forprivate land. The State may have acquired property through a reversionary deed. A reversionarydeed grants ownership only until a specific date or event occurs. Upon reaching the specifieddate or when the event occurs, the property goes back (or reverts) to the owner who conveyed theproperty. The State may also own land through real estate tax forfeiture. These lands areadministered for the State by the county. State mineral ownership includes two additionalcategories: severed mineral tax forfeiture and non-registered severed mineral forfeiture. Severed

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A township contains 36 sections, 1 mile square

A section generally consists of 16 quarter-quarters (or forties)

Figure 3. Description of a section, government lot, and township.

mineral tax forfeiture is a forfeiture for nonpayment of the severed mineral interest tax. Non-registered severed mineral forfeiture is a forfeiture for failure to file the required statement ofsevered mineral interest within the required time specified by statute. The State is deemed to bethe owner of non-registered severed minerals upon the failure to file the statement. However, theState’s ownership is not absolute until a final forfeiture judgment is made by the courts.

Stockpile Ownership The ownership of stockpiled material is difficult to determine since ownership depends upon theintent of the parties involved at the time the stockpile was created. The intent of the parties maybe revealed through examining documents such as leases, operating agreements, stockpilingagreements, and commingling agreements.

When minerals are severed from their natural bed with an intention that the minerals be disposedof as other than real property, a conversion occurs, and the minerals become personal property.(“Real property” refers to the land itself and whatever is affixed to the land. “Personal property”generally refers to all property other than real estate.) This personal property conversion canoccur with stockpiled materials which were stored for possible future use. One problem that canarise is when materials are stockpiled on land not owned by the owner of the stockpiledmaterials. This occurrence can produce separate ownership of the underlying real estate and thestockpiled materials, which now constitute the visible surface of the land. Similarly, if the realproperty on which the stockpile is located is conveyed without specifically including all personalproperty located on the parcel, the stockpiled materials may not be conveyed to the new owner ofthe real property. There are instances, and probable instances, where stockpiles within the study

areas have different owners than that of the underlying surface real estate.

Most of the documents necessary to determine stockpile ownership are not available for publicreview. Many private mining leases and agreements, which may provide information onstockpiles, are not recorded in the official county land records. The ownership informationgathered for this project was based upon the best available information accessible to the DNR,Division of Lands and Minerals. Information was located in documents filed in county landrecords, State mining records, and information provided by private mining companies with landholdings in the two study areas.

Numerous stockpiles are still actively managed by mining companies and other private owners. Information was obtained from these companies/owners regarding the stockpiles they own andmanage. Stockpiles of surface material, or overburden, is generally thought to have the sameownership as that of the surface estate on which it is now located. This material was removedthrough mining to gain access to the mineral wealth below, thus there was no intent to create aseparate personal property interest. Many stockpiles still have undetermined ownership. Theownership of these stockpiles may be determined by locating an agreement between privateparties or by tracing the mineral owner of the material back to the property from which it wasmined. This project made an effort to locate such documentation and to trace the mineral ownerof the stockpiled material back to the mined property without success.

B. STOCKPILE MATERIAL INVENTORYSeveral steps were taken throughout the stockpile inventory portion of the project. First,information was gathered to determine the composition of stockpiled material. Then aclassification system was designed to incorporate all the types of material encountered in the twostudy areas. To define the location of the stockpiles, an outline, or “footprint”, of each stockpilewas digitized and labeled. The samples taken from the assorted stockpile material types wereanalyzed. Volumes for some of the stockpiles were estimated.

Stockpile Composition The determination of stockpile composition, or material type, was based on many sources ofinformation. These sources were given a hierarchical rank of importance, which was then usedto determine the material type of a particular stockpile. Reviewed below are the sources ofinformation and methodology used to determine the material type, listed in order of importance.

Company InformationPre-existing information about stockpiles was a key factor in determining the material type. Information, such as iron units and volume, were calculated and values assigned as a stockpilewas being built. This information was found to be more reliable than any comparable stockpilesampling technique. Stockpiles can be large in size, contain different ore grades, and thematerial can be cumbersome to sample. So the importance of pre-existing records is the result ofhow difficult it is to “represent” a stockpile by sampling. For these reasons, specific informationpertaining to a single pile was obtained solely from company records.

This information was gathered with the cooperation of several stockpile owners by providing

them with a list of stockpiles that referenced common names or locations of stockpiles. This listapplied primarily to iron ore stockpiles. Detailed information such as iron, silica, and aluminumcontent, and volume was provided. The accuracy of these records could vary between sources;however, they are the best available information.

Field WorkMost stockpiles (over 95%) were visited in the field. The primary purpose of the field work wasto confirm the material type, sample the material when possible, and photograph various piles. Stockpiles were described using the guidelines:

• Material type (glacial overburden, natural ore, fine tailings)• Mineralogy (identifying iron ore minerals, such as hematite, magnetite, goethite, etc.)• Range of rock size within the pile• Approximate average rock size• Rock angularity• Sorting of stockpile• Estimated amount of sand and gravel the pile may contain• Other observations and comments

Where no company information was available for a stockpile, field descriptions were the nextbest source of information. The limitation to observing stockpiles in the field is that onlyportions of the surface of the pile can be observed. This was especially true for glacialoverburden stockpiles where vegetation was dense and soil development was thick. Anotherlimitation to observing the stockpile surface is that the visual portion represents only a smallpercent of the total stockpile volume. Therefore, it is important to note different material typesmay be present within the stockpile.

Various stockpiles were sampled throughout the two study areas. The purpose of sampling wasprimarily to obtain a range of results for various stockpile material types. Aggregate tests wereconducted on most samples, and chemical assays were conducted only on the iron ore bearingmaterials. This approach was taken because of the difficulty associated with representativesampling of stockpiles. Of all accepted sampling techniques, stockpile sampling is the leastaccurate (Minnesota Department of Transportation Aggregate Production I, 1998). Therefore,the sampling methodology of this project is geared towards showing the range of values that maybe encountered while working with a specific material type. The object of the test results is tohelp determine what type of material would suit a particular use. Once a material type is chosen,additional testing of a particular stockpile may be required by the user to determine if thatstockpile meets the desired needs and specifications.

The samples were collected as random grab samples. For stockpiles, a 20 pound sample wastaken at the surface or at an edge of a pile using a small shovel. For tailing basins, a hand augerwas used with a 4-inch diameter bucket and samples were obtained by auguring approximately 3feet down from the surface. This produced roughly a 20 pound sample. The sample sites werechosen by ease of access to the piles and material type. Stockpiles that were not accessible bytruck were not sampled. In basins, the “finer” (silt and clay sized particles) portions are very

densely vegetated while the sandier portions are open. For this reason, the coarser areas oftailing basins were sampled more frequently. There were two reasons a stockpile material typewas not sampled. The material was either too large to fit into a sample bag (+2 feet) or thematerial was known to be a poor aggregate. For example, slate and paint rock are considered tobe spall or substandard rock; thus, neither were sampled.

Photographs were taken of several stockpiles. The purpose was to give a visual aspect to thestockpiles. All samples and photograph locations were gathered using a Global PositioningSystem (GPS) unit. The accuracy of each location is within 15 meters. Other observation pointswere also collected. These were located by either GPS or aerial photography techniques.

Aerial Photographic InterpretationTo further confirm observations made in the field, several sets of aerial photographs wereinterpreted. Material types could be differentiated in the air photo by identifying certain materialcharacteristics. For example, overburden piles were light in color and rock piles were dark;tailing basins appeared to have a network of water channels that resembled “veins” when theywere active; and large rock piles had a “bumpy” texture. However, some distinctions could notbe determined (i.e., the differences between two types of ore). For the Virginia site thefollowing aerial photographs were used:

• MNDNR Color Infrared 1997 (1:15,840)• NAPP Color Infrared 1991 (1:40,000)• Black and White 1961 (1:40,000)• Black and White 1947 (1:40,000)

For the Calumet site the following aerial photographs were used:• MNDNR Color Infrared 1995 (1:15,840)• NAPP Color Infrared 1991 (1:40,000)• Black and White 1969 (1:80,000)• Black and White 1966 (1:40,000)

Mining MapsThere are three sets of mining maps that were consulted when identifying stockpiles: the 1982USX Plates and the 1955 and 1959 editions of the Great Northern Iron Ore Properties’ Map ofthe Mesabi Range. These maps helped identify commonly known stockpile names, confirmsome material types, and show footprints of some stockpiles. The maps and aerial photographsalso helped identify the relative age of the stockpiles.

Stockpile Material ClassificationIn the process of gathering pre-existing information from mining companies and assemblinginformation gathered in the field, it was apparent there were several different material typeclassifications used by various mining companies. One material type could have several different“material type” labels. Some examples are:

Lean Ore versus Lean MaterialTaconite versus Taconite Rejects versus Taconite Dumps versus Lean TaconiteHeavy Media versus Cone Tailings versus Jig Tailings

Figure 4. Schematic diagram of stockpile classification system. The material types are somewhatarranged by the stratigraphy as seen in the field.

Within each example above, the materials are very similar. Although various classifications mayhave specific meaning to a particular mine, or process, or an indication of iron content, they maynot be applicable in both study areas. On a broader scale, these classifications cannot be usedRange-wide with certainty. Therefore, a classification system was developed specifically for thisproject. It represents an attempt to look at stockpiled material in a broader view so that materialtypes can be generalized yet accurately represented. If a similar stockpile inventory were to beconducted for the entire Mesabi Iron Range, it would be most useful if a universal materialclassification system was developed. The classification system used in this project combinesgeology and iron content (mining practices) to differentiate stockpile material types.

There are approximately 10 material types (Figure 4). The types are initially broken down bygeologic type: bedrock versus unconsolidated sediment. Unconsolidated sediment is generallyconsidered overburden in the mining industry. Two types of overburden were observed: glacialand Cretaceous. There are some bedrock units that can be considered overburden. An exampleis the Virginia Slate that overlies the iron formation. However, there are several slaty unitswithin the iron formation. In the classification system, slate stockpiles were not labeledoverburden because they may contain slate mined from within the iron formation.

Bedrock and sediment is then subdivided by the “intent of mining” (i.e., not mined for iron unitsversus mined for iron units). Although the material types of “paint rock” and “slate” may containsome iron units, for the purposes of this project, they were not considered to be an iron ore. The

material types that fall under “mined for iron units” are: Cretaceous ore, natural ore fine tailings,natural ore coarse tailings, natural ore mixed-sized rock, taconite mixed-sized rock, and taconiteboulders. These material types were designed to include the following range of materials:

Coarse tailings - includes cone tailings, jig tailings, and heavy media rejectsTaconite boulders - includes taconite, taconite rejects, taconite dumps, lean taconiteNatural ore mixed-sized rock - includes lean ore, natural and wash ore, and lean ore

material (magnetic).

Aggregate TestingA total of 82 samples were taken of various stockpile materials. For aggregate testing, most ofthe samples were sieved to determine the gradations of particle size. This test was conducted atthe DNR Hibbing Laboratory using methodologies specified by the Minnesota Department ofTransportation (MNDOT). Some samples were too fine to sieve; these samples includednumbers 45 and 46. To test the material thoroughly with as many aggregate quality tests aspossible, samples were composited. This process combines several samples into one. Forexample, samples 53, 54, 55, 56, and 57 were combined to form composite A1. Thencomposites A1, A2, A3, and A4 were combined to form composite ZZ1(Table 1). For the mostpart, composited samples are within the same stockpile. In other cases, samples from manystockpiles, that were the same material type, were combined. The aggregate testing wasconducted at Braun Intertec Corporation, Minneapolis, Minnesota. The aggregate tests are listedby material type in Table 2. (An explanation of the individual aggregate tests and location mapof the samples are found in Appendix A).

Iron Ore TestingFor iron ore testing, chemical assays were completed on a total of 51 iron ore samples. Thetesting was conducted at Midland Research Center, Nashwauk, Minnesota. The chemical assaysperformed on each sample determined the amount of major oxides, which helped to characterizethe material type.

Table 1: Sample list by material type.

MATERIAL TYPE PILE # SAMPLES COMPOSITE 1 COMPOSITE 2A. Coarse Tailings 418 53, 54, 55, 56, 57 A1

419 49, 50, 51, 52 A2 ZZ1424 43, 44 A3 Includes A1-A4

429 39, 40, 41, 42 A4313 27 A5362 18, 19, 20, 21 A6 ZZ2

369, 374 68, 69 A7 Includes A5-A8

430 79, 80 A8

B. Cretaceous Ore 373, 361, 336 17, 22, 23 B9 ZZ3C. Fine Tailings 340 58, 59, 60, 82 C10

327 61, 62, 63 C11 ZZ4325 64, 65 C12 Includes C10-C12

417 45, 46 C13 NOT TESTED

432 35, 36, 37, 38 C14417 47, 48 C15 ZZ5335 29, 30, 31 C16 Includes C14-C16

302 24, 25, 26 C17423 76, 77, 78 C18 ZZ6396 81 C19 Includes C17-C19

D. Glacial Overburden 409 70, 71, 72, 73 D20360 66 D21 ZZ7305 28 D22 Includes D20-D22

402 75 D23353 33, 34 D24 ZZ8372 67 D25 Includes D23-D26

154 1* D26130 2, 3, 4, 5 D27 ZZ9168 6, 7, 8, 9 D28 Includes D27-D29

Not a pile 11, 12, 13 D29

E. Mixed-Sized Rock 174 14, 15 E30(Taconite & Natural Ore) 411 74 E31 ZZ10

339 32 E32 Includes E30-E32

Table 2. Tests performed on each sampled material type.

TESTNUMBEROF TESTS

COMPOSITE 1 COMPOSITE 2

A. Coarse Tailings

Specific Gravity (Coarse and Fine) C127 and C128 8 A1 through A8

Absorption (Coarse and Fine) C127 and C128 8 A1 through A8

Flatness and Elongated D4791 8 A1 through A8

Clay Lumps C142 8 A1 through A8

Abrasion C88 2 ZZ1 and ZZ2

Soundness C131/C535 2 ZZ1 and ZZ2

B. Cretaceous Ore

Specific Gravity (Coarse and Fine) C127 and C128 1 B9

Absorption (Coarse and Fine) C127 and C128 1 B9

Clay Lumps C142 1 B9

Abrasion C88 0 Not enough sample

Soundness C131/C535 1 ZZ3

C. Fine Tailings

Specific Gravity (Fine) C128 9 C10 through C19

Absorption (Fine) C128 9 C10 through C19

Fine Aggregate Particle T304 3 ZZ4, ZZ5, and ZZ6

D. Glacial Overburden

Specific Gravity (Coarse and Fine) C127 and C128 10 D20 through D29

Absorption (Coarse and Fine) C127 and C128 10 D20 through D29

Flatness and Elongated D4791 10 D20 through D29

Clay Lumps C142 10 D20 through D29

Spall (MNDOT) 10 D20 through D29

Lightweight Particles C123 10 D20 through D29

Abrasion C88 3 ZZ7, ZZ8, ZZ9

Soundness C131/C535 3 ZZ7, ZZ8, ZZ9

E. Mixed-Sized Rock

Specific Gravity (Coarse and Fine) C127 and C128 3 E30 though E33

Absorption (Coarse and Fine) C127 and C128 3 E30 though E33

Flatness and Elongated D4791 3 E30 though E33

Clay Lumps C142 3 E30 though E33

Soundness C131/C535 1 ZZ10

Stockpile DigitizingThe footprints of the stockpiles were digitized to capture the geographic location and areal extentof each stockpile. This was necessary to map the material types as well as to determine stockpileownership. The footprints of the stockpiles were derived from two sources. The majority of thelines were digitized within this project using the terms and definitions specific to this project. Where applicable, lines from a mining features layer that is currently in-progress at the DNR,Division of Lands and Minerals were used.

For this project, digitizing was based on an existing dataset called the Mesabi Iron RangeElevation Project. This data set includes 1998 digital orthophoto quads (digital air photographs),elevation contours at a 5 foot interval, and lines that highlight breaks of slope. The digitizingwas conducted at a scale of 1:4,000 and was completed in February, 2001. The stockpiles wereassigned numbers within each study area. Virginia stockpiles are numbered 101 to 198; Calumetstockpiles are numbered 301 to 434.

Volume EstimationStockpile volumes were estimated for some stockpiles in loose cubic yards. The estimates werecalculated by a surficial mapping software program (Surfer), using data from the 1998 MesabiIron Range Elevation Project. Only some piles were chosen for the volume estimations. Thiswas due to the difficulty of modeling the bottom surface of many stockpiles. Since theunderlying topography below a stockpile is generally unknown, and directly affects a volumeestimate, a primary assumption was made for modeling purposes:

All stockpile volume estimations are based upon a flat, planar, bottom surface.

Therefore, a flat, planar, bottom surface was captured by using the surrounding elevationadjacent to the stockpile edge. By capturing the elevation where the stockpile met the naturaltopography, the bottom plane can be thought to retain the natural slopes or dips in the naturaltopography. If a pile was built into a hill or adjacent to another pile, the bottom slope could notbe obtained; therefore, the pile was not estimated.

The upper surface of a pile was modeled using elevation points from the Mesabi Range ElevationProject. The elevation data was derived from pre-existing survey points donated by the miningcompanies and 1998 aerial photography. From the elevation information, 5 meter grid pointsthat contain the x, y, and z coordinates were utilized. Using this grid, the upper and lowersurface of the pile was modeled. Listed below are the modeling parameters implemented toobtain the upper and lower surface of a stockpile:

• Gridding Method: Kriging• Spacing: 5 meters• Variogram Model: Linear• Search Radius: No search radius, all surrounding data was used.

Both surfaces were “blanked” or trimmed to the footprint of the stockpile. The volume was thencalculated by determining the cubic yards between the upper and lower surface.

C. DATABASE DESIGNThe database was designed with three goals in mind: (1) capture the results of the research(material type, ownership, sampling, etc.), (2) capture the results so the information could bequeried and browsed from many different viewpoints, and (3) mirror “real world” relationshipswithin a relational database structure. To our knowledge, this is the first attempt at modeling anddeveloping a database design that would accommodate the complexities of stockpiles andownership on the Mesabi Iron Range. To develop a database design that would accommodate thecomplexities of stockpiles on the Range required the use of a structured data modelingmethodology. There are many benefits to using a relational structure for the database design. From the modeling and analysis sessions, a common vocabulary develops that facilitatescommunication within the project group. Breaking down the information into the smallestpossible parts allows knowledgeable database users to combine, compare, and analyze the largestpossible combination of factors. Data stored in this manner also allows the structure to be quitestable, which gives the application developers greater flexibility for design. To accomplish thesegoals, a structured data modeling methodology was required. The chosen methodology was amodified version of project development created by Advanced Strategies, Incorporated ofAtlanta, Georgia (Technical Data Modeling, 2000).

From the onset of data modeling, it was clear the database would be a prototype. Thedevelopment stage required several modeling sessions to develop the Business Object Model,Conceptual/Logical Data Model, and Physical Data Model (Appendix B). The process ofdesigning this database required a clearly outlined project definition (Appendix C). Thisdefinition partially addresses the following questions:

• What type of information was to be put in the database (i.e., sample locations, surfaceownership by forty, the volume of a stockpile)?

• What type of information was to be extracted from the database (i.e., How manyglacial overburden stockpiles does the state own? Are there any samples of thisstockpile? If so, what are the aggregate results)?

• Who will be asking the questions (i.e., a landowner, an aggregate contractor, otherstate and local governments)?

After these sessions, it was clear that the database needed to be designed solely for data input andstorage. Any further development, like a “point and click” interface (as seen on the Internet)would be like putting a prototype straight onto a production line. This also allowed the focus ofthe project to accurately capture all of these “real world” data sets that were encountered withinthe two study areas, and to hammer out their convoluted relationships. In addition, thegeographical information (i.e., outlines and labels of digitized stockpiles) had to relate toinformation stored in the database. The resulting database was implemented using MicrosoftAccess 97. The corresponding geographical information was captured using ArcView 3.2.

It is important to note that the data are meant to capture a snapshot in time, and there are no plansto maintain or update the database. This decision impacted the database design in a couple ofways. First, historical information, such as the chain of title for each property is not included.Secondly, the data structure is simplified when collected information does not need to be tracked

and stored over time. Also, if this project expands into a Range-wide study, the database wouldneed certain modifications. One reason for modification may include new relationships that werenot encountered within the two study areas.

D. STOCKPILE ACCESSThe intent of this section is to provide users an estimate of the type of access to stockpiles,considering vegetation cover and existing roads. This allows stockpiles near majortransportation routes and/or covered by thick vegetation to be identified. Access is notnecessarily a limiting factor because it can be improved. Reviewed below is the methodologyused to create a stockpile vegetation layer and a transportation layer.

VegetationVegetation cover of stockpiles can affect the use of stockpiles. For example, extensivereclamation projects have been conducted on some stockpiles. Reclaimed stockpiles can beidentified by the type of vegetation covering the stockpile. Also, some of the stockpiles are veryold, which has resulted in a dense vegetation cover. Where this occurs, timber harvesting couldbe one method of exposing the area that would utilize all resources associated with a stockpile.

Vegetation layers for both study areas were digitized using ArcView and a combination of aerialphoto interpretation and field checks during the fall of 2000. Vegetation was delineated forstockpile areas using color infrared aerial photographs (dated September 1995 for the Calumetsite, and September 1997 for the Virginia site) with a 1:15,840 scale. Major forest vegetationcover types were determined to be aspen-birch (in order of prevalence: aspen, paper birch, andbalsam poplar) and conifers (in order of prevalence: red pine, jack pine, balsam fir, white spruce,and white cedar). Generally, the aspen-birch cover type was naturally occurring; whereas, themajor conifer cover types were plantation-planted red pine and jack pine. Size classdeterminations were based upon merchantability of the stand within a cover type. If the majorityof trees in a stand had over a 50% canopy cover and an average diameter at breast height (dbh)greater than 5 inches, it was viewed as merchantable. Stands containing a majority of trees in thecanopy with a dbh less than 5 inches were viewed as non-merchantable. Open areas were alsodelineated. These areas included barren ground, open water, grasslands, shrubs, or treereproduction areas (less than 1 inch dbh), and any forest canopy with less then 50% cover.

TransportationBecause aggregate is a high bulk, low value commodity, a travel distance of 20 to 30 miles candouble the transportation costs (Aggregate Task Force, 1998). Therefore, the currenttransportation infrastructure was mapped during the summer of 2000. Private mining roads weredigitized and classified. The classification is based upon current conditions and if the road is arailroad grade. The two road types are roads in “good to moderate” and “poor to moderate”condition. Good to moderate condition implies the road may be used as is or with somemodifications. Poor to moderate condition implies the road needs many to some modifications. The modifications may include widening and/or grading the road to rebuilding it due to washouts. Railroad grades and old railroad grades are mapped to show the potential use of rail to transportstockpiled material. Many old railroad grades have had ties removed and are currently being usedas roads. In some instances, railroad ties are still in place. The transportation layer was mappedsimilarly to the stockpile footprints. The scale of mapping was done at 1: 4,000.

IV. RESULTSA. OWNERSHIP

Surface and Mineral OwnershipSurface and mineral ownership were determined for all parcels within the two study areas. Atotal of 2,839.32 acres was researched in the Virginia study area. A total of 4,067.02 acres wasresearched in the Calumet study area. Surface and mineral ownership were updated for anadditional 2,498.99 acres in the Calumet site that had been previously researched by the DNR,Division of Lands and Minerals. Parcels platted into lots and blocks were not researched.

The project database provides detailed information regarding the surface and mineral ownershipfor each parcel within the two study areas. Ownership within the database is organized byTownship-Range-Section and is detailed to the forty-acre parcel or government lot. All parcelswithin the Virginia site are within Township 58, Range 17. Parcels within the Calumet site arewithin either Township 56, Range 23 or Township 56, Range 24. Parcels divided betweenmultiple owners have owners listed with the description of the portion of the parcel they own. Many parcels have multiple owners, each owning an undivided, fractional interest in the parcel. For these parcels, each owner is listed along with the fractional interest owned. Surface andmineral ownership are only as accurate as of the date the title work was conducted for the parcel. Ownership changes may have taken place since the parcel was researched. Surface and mineral owners have been identified in the project database. Private individualowners have not been named. These owners have the designation “private” when one individualis involved, or “many private” when more than one individual is involved. Platted areas, such aswithin the cities of Calumet and Marble, were not researched and have surface and mineralownership listed as “undetermined.” For parcels that have an ownership interest by the State ofMinnesota, the means by which the State became the owner is also provided. State ownershipcan be through the following means: trust fund, acquired, exchange, tax forfeiture, reversionarydeed, and non-registered severed minerals. For non-registered severed minerals, the owner waslisted as “undetermined” rather than the State. This is because the State’s ownership in suchminerals has yet to be judged as absolute by the courts. (See Ownership Methodology foradditional information regarding means of State ownership).

Plates I and II show a generalization of the surface and mineral ownership in the Calumet andVirginia study areas. Some owners have been grouped together for simplicity in mapping. Thesemaps are not to be relied upon for exact ownership. Exact ownership for each parcel can befound in the database. Ownership is mapped to the forty-acre parcel or government lot. Railroadright-of-way ownership has not been mapped. Any ownership, from one acre to the entire parcel,by the State of Minnesota, through any means, takes precedence in deciding the mapping unit. An explanation for the mapping units used to depict surface and mineral ownership follows.

State - State of Minnesota owns the parcel through any means, except through a realestate tax forfeiture.

County Real Estate Tax Forfeit - State of Minnesota owns the parcel through real estatetax forfeiture; county administers the land for the State.

Other government - the parcel is owned by a government entity other than the State. The

government owner may be county, city, tribal, or regional in nature.[Mining company name] - the parcel is owned by the named mining-related company.

The companies specifically named are Cliffs Biwabik Ore Corporation, GreatNorthern Iron Ore Properties, Inland Steel Mining Company, LTV Steel, M.A. HannaCompany, Rendrag, Inc., and USX.

Private - the parcel is owned by one individual or one non-mining company. Non-miningcompany refers to any company that is not one of the seven mining-related companiesnamed above.

Many private - the parcel is owned by two or more individuals or non-mining companies.Part State and other - State of Minnesota owns a portion (1-99%) of the parcel, through

any means other than a real estate tax forfeiture, and one or more others own theremainder of the parcel. The other owner can be any combination of the abovemapping units.

Part County Real Estate Tax Forfeit and other - State owns a portion (1-99%) of theparcel through real estate tax forfeiture along with one or more, other, non-Stateowners.

Part Mining Company and other - one of the seven named mining-related companies (seelist above) owns a portion of the parcel along with one or more, other, non-Stateowners.

Undetermined - platted property; surface and mineral ownership not researched.Non-registered severed minerals - Absolute ownership by the State of Minnesota to all

minerals upon completion of forfeiture action, due to the mineral owner not filingtheir statement of severed mineral interest.

Stockpile OwnershipStockpile ownership can be difficult to determine. Ownership of stockpiles is dependent uponthe intent of the parties at the time the stockpile was created. (See Ownership Methodology forinformation regarding how stockpile ownership is determined). A best effort was madethroughout this project to determine the owners of all stockpiles within the two study areas usingavailable sources. Ownership was determined for a majority of the stockpiles located within thestudy areas. However, many stockpiles still have undetermined ownership. The ownershipremains undetermined since the intent of the parties could not be discovered. No documentationpointing to ownership was found. Absent documentation, the stockpile ownership may bedetermined by tracing the mineral owner of the stockpiled material back to the property fromwhich it was mined. This also proved to be a difficult task, since this information was oftenunavailable.

Stockpile ownership in the database is organized by forty-acre parcel or government lot. However, unlike surface and mineral ownership, stockpiles are not confined to the boundaries offorty-acre parcels or government lots. To resolve this conflict, the database identifies eachstockpile with an identification number. A unique number (referred to in the database as the“PLS intersected stockpile ID) is assigned to each portion of a stockpile that lies within aparticular forty-acre parcel or government lot. Ownership of a stockpile may be the same for theentire stockpile, thus all polygons connected to this stockpile will have the same owner. Acheckbox in the database indicates whether an ownership entry applies to the entire stockpile. Overburden stockpiles have their ownership tied to the underlying parcel’s current surface estate

owner. Therefore, each area of these overburden stockpiles may have different owners, resultingin a fragmented ownership across forty-acre or government lot boundaries. A checkbox in thedatabase indicates whether an ownership entry is connected to the surface ownership.

The owner for each portion of a stockpile is listed in the database according to the PLSintersected stockpile ID number. As with the surface and mineral ownership, private individualowners have not been named in the database. These owners are designated as either “private”when one individual is involved, or “many private” when there are two or more individuals. Stockpiles listed in the database as having “undetermined” ownership are those in whichdocumentation regarding stockpile ownership could not be found or the mineral owner of thematerial could not be traced back to the mine from which it was removed. State-ownedstockpiles also list the means by which the State became the owner.

Plates I and II show a generalization of ownership for all stockpiles located within the Calumetand Virginia study areas. Ownership has been condensed into ownership groups for simplicity. The maps are not to be relied upon for exact determinations of stockpile ownership. Thedatabase should be consulted for precise information about each stockpile’s ownership. Forthose stockpiles in which ownership is connected to the underlying surface ownership, thestockpile ownership may appear fragmented across forty-acre or government lot boundaries dueto changes in ownership.

Stockpile ownership is mapped using the same mapping units as those used for mapping surfaceand mineral ownership. As with surface and mineral ownership, any ownership by the State ofMinnesota, through any means, takes precedence in deciding the mapping unit. Definitions ofthe mapping units used for the stockpile ownership are as follows:

State - State of Minnesota owns the stockpile through any means, except through a realestate tax forfeiture.

County Real Estate Tax Forfeit - State of Minnesota owns the stockpile through realestate tax forfeiture; county administers the land for the State.

Other government - the stockpile is owned by a government entity other than the State. The government owner may be county, city, tribal, or regional in nature.

[Mining company name] - the stockpile is owned by the named mining-related company. The companies specifically named are Cliffs Biwabik Ore Corporation, GreatNorthern Iron Ore Properties, Inland Steel Mining Company, LTV Steel, M.A. HannaCompany, Rendrag, Inc., and USX.

Private - the stockpile is owned by one individual or non-mining company. Non-miningcompany refers to any company that is not one of the seven mining-related companiesnamed above.

Many private - the stockpile is owned by two or more individuals or non-miningcompanies.

Part State and other - State of Minnesota owns a portion (1-99%) of the stockpile,through any means other than a real estate tax forfeiture, and one or more others ownthe remainder of the parcel. The other owner can be any combination of the abovemapping units.

Part County Real Estate Tax Forfeit and other - State owns a portion (1-99%) of the

stockpile through real estate tax forfeiture along with one or more, other, non-Stateowners.

Part Mining Company and other - one of the seven named mining-related companies (seelist above) owns a portion of the stockpile along with one or more, other, non-Stateowners.

Undetermined - stockpile ownership is undetermined. The owner of the stockpile may bedetermined by locating a stockpile agreement (if one exists); or if the mine of origin isknown, by determining the mineral owner of the stockpiled material.

B. STOCKPILE MATERIAL INVENTORYThe results of the stockpile inventory of material type are summarized in Plates III and IV. Theplates show the stockpile outlines in relationship to the material type, stockpile identificationnumber, sample locations, photograph locations, and observation points. A total of 232stockpiles were inventoried: 98 in Virginia and 134 in Calumet. A breakdown of the number ofstockpiles by material type is as follows:

70 Taconite Rock (Boulders)65 Glacial Overburden32 Natural Ore Mixed-Size Rock24 Natural Ore Fine Tailings14 Natural Ore Coarse Tailings13 Taconite Mixed-Size Rock6 Paint Rock5 Cretaceous Ore2 Cretaceous Overburden1 Slate

Company records for iron units were obtained for 73 stockpiles. Therefore, approximately 43%of the iron-bearing stockpiles (excluding glacial overburden and slate) have some detailedcompany information. Volume estimates were completed for 22 stockpiles.

Stockpile Material DescriptionsFor the stockpile material type classification system, a brief description was created for eachmaterial type. This description is an attempt to describe and classify material observed in thefield.

Glacial Overburden: This includes unconsolidated sediment deposited by glaciers that wasremoved to gain access to the iron ore. Material consists of sediments deposited during theQuaternary Period (10,000 to 2 million years ago). The sediments range from till (materialdeposited directly by glacial ice) to sand and gravel (material deposited from glacial meltwater). Till is an unsorted sediment with grain sizes ranging from clay to +5 foot boulders. Multipleglacial advances deposited several till units in the region. Between some of these till units are

Figure 5. Picture of glacial till. Note the grain size ranges from silts toboulders. Twelve inch ruler is for scale.

discrete lenses of sand and gravel. In several overburden stockpiles, many of these various unitsare mixed together. The stockpiles tend to be boulder-rich with a sandy, silt matrix (Figure 5). The color ranges from buff to reddish-brown. Rock particles are sub-angular to sub-rounded. Afew stockpiles contain primarily outwash sand and gravel. The sand and gravel is moderatelysorted, oxidized to a light brown color, contains little silt, and is cobble-rich. The rock particlesare sub-rounded.

Cretaceous Overburden: This includes unconsolidated sediment in the form of saprolitic clayand rock particles that forms from chemically weathered iron formation. Weathering eventsoccurred during the Cretaceous period (65 to 146 million years ago). This material dominantlycontains clay with some rock particles. Within a given stockpile, Cretaceous overburden maycontain glacial till and other “overburden” type sediments.

Cretaceous Ore: Semi-lithified conglomerate deposited during the Cretaceous period. Theconglomerate contains sub-angular to rounded hematite cobbles and sands within an iron-rich,glauconitic, carbonate matrix. Cretaceous ore piles have moderately poor sorting and range ingrain size from clay to 3 foot boulders. The boulders are highly cemented blocks of smaller rockparticles.

Figure 6. Picture of material called slate. Fractures occur along bedding planes. Pen is forscale.

Slate: A local term used to described a fine-grained rock composed mostly of siliceous minerals. Slate is found above and within the iron formation and is approximately 1.9 billion years old. Although the slate is mostly fine grained, some clastic bedding is evident. Fracturing, orsplitting, occurs along bedding planes (Figure 6). Within the pile, slate appears to have a darkgrey appearance. Rock sizes range from 1/8 of an inch to +3 feet.

Natural Ore Mixed-Sized Rock: This includes soft iron ore that has been altered and re-mineralized along faults and fractures. This material was originally taconite, which was thenoxidized to create trough, fissure, or flat-lying natural iron ore bodies. The mineralogy consistsof mostly hematite, goethite, and limonite, with minor amounts of magnetite and manganeseoxides. There are a range of textures from compact to rubbly or friable. Bedding and otherprimary features are often evident. Within a stockpile, this material is unsorted. Rock sizesrange from clay to +6 foot boulders with an estimated average rock size being 3/8 of an inch to 5inches. The amount of clay in natural ore piles is difficult to quantify; however, the clay seemsto be a natural cement that stabilizes the stockpile. Natural ore rocks fracture, or part, parallel tobedding planes. Taconite boulders are frequently observed along the slopes of natural orestockpiles and may have been placed there for slope and erosion control.

Figure 7. Picture of coarse tailings. Note the range ofmaterial size. Shovel is 2 feet long.

Natural Ore Coarse Tailings: This includes a by-product of the natural iron ore miningprocesses. This by-product contains mostly siliceous rocks with some hematite banding. Thestockpiles are moderately-well sorted, ranging in size from 3/8 to 4 inches in diameter, and hasan angular particle shape (Figure 7). In the processing of coarse tailings, the material was

washed; therefore, there is little to no siltwithin the pile.

Natural Ore Fine Tailings: This includes a by-product of the natural iron ore miningprocesses. Fine tailings have been crushed andusually deposited into a “tailings” basin. Thismaterial is very well sorted with a rock sizeranging from clay to 3/8 of an inch. Rockfragments are sub-angular.

Paint Rock: A highly decomposed, slate-likerock with a tacky, powdery texture on exposedsurfaces. The decomposition of these rocks isattributed to weathering of altered slate andnatural ore along fault or joint planes. Thedescriptor “paint” refers to the red to rustcolored, colloidal particles that partiallyconstitute the rock. Within the stockpiles,paint rock can range from fine sand to +3 footrocks. Similar to natural ore, paint rockfractures parallel to bedding planes.

Taconite Rock Boulders: This includesmagnetic and some non-magnetic iron-bearingboulders. Characterized by alternating bandsof iron oxides (magnetite and/or hematite) with

bands of silicates and carbonates. Bedding and other primary structures are evident. Mosttaconite stockpiles consist of boulder-sized rocks ranging from 2 feet to +9 feet in diameter withan estimated average of three feet. The boulders tend to have a blocky shape. Some glacialboulders may be incorporated into the pile.

Taconite Mixed-Size Rock: Magnetic and non-magnetic iron ore, some of which may have beenprocessed. The rock characterization is described in Taconite Rock Boulders above. Thisstockpile type is difficult to discern from “Natural ore mixed-sized rock” in the field and maycontain other material within the stockpile; classification is based upon company recordspertaining to individual stockpiles. These piles are poorly sorted with a rock size from 2mm to+6 feet. Taconite boulders frequently occur along the slope and edges of these piles.

Aggregate Testing ResultsThe aggregate testing results are separated into two parts: material overview and materialcomparison by tests. The material overview presents all aggregate testing results categorized bymaterial types. Under each of the material types, there are two tables. The first table shows theresults of Composite 1 (composited samples, as listed in Table 1). For some of the aggregatetests, the MNDOT specifications for general aggregate use are listed under the “Spec” column(MNDOT Standard Specifications for Construction, 1995). The second table shows the resultsof Composite 2 (composite of composites, as listed in Table 1).

The sampled material types are then compared to each other using the results from fourindividual tests. These four tests include specific gravity, absorption, soundness (magnesiumsulfate), and gradations.

Glacial Overburden-• Gradations: In general, glacial overburden piles contain abundant fine sands and silts.

Some piles consisting of mostly glacial outwash (rather than glacial till), may fallwithin Class 5 specifications.

• Absorption: Absorbs little to moderate amounts of water (Table 3).• Specific Gravity: Results fall within a tight range of one another. This result was a bit

surprising because samples were taken from both study areas. • Clay Lumps: Meets specifications.• Shale: Within specifications for both fine and coarse aggregate.• Total Sum of Spall: Within specifications.• Soft Iron Oxides: Results vary; some samples are within specifications.• Soundness (Magnesium Sulfate): Within specifications. Sample ZZ8 has a higher

value due to the inclusion of iron ore in composite (Table 4).• Abrasion: Within specifications.• Field Observations: There are abundant stockpiles of this material type. The

stockpiles are generally boulder-rich.

Table 3. Composite 1 results for testing glacial overburden material type.Composite 1 D20 D21 D22 D23 D24 D25 D26 D27 D28 D29 Specs

Tests ZZ7 ZZ8 I.O.* ZZ9

Shale ASTM +1/2" 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4

+ #4 total 0.1 0.1 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.7

Soft Iron Oxide 0.2 0.5 1.6 0.1 0.8 0.6 1.1 0.2 0.4 0.1 0.3

Chert 0.0 0.0 0.1 0.1 0.1 0.0 0.0 0.0 0.0 0.0 3.0

Total Spall +1/2" 0.0 0.2 0.4 0.0 0.3 0.9 0.2 0.2 0.1 0.0

+ #4 Total 0.3 1.8 2.3 0.7 1.3 2.4 2.3 0.4 0.4 0.1

Soft Particles 0.8 0.4 0.0 NA 0.6 0.1 0.7 0.4 0.0 0.0

Clay Balls & Lumps 0.3 0.3 0.3 0.5 0.5 0.5 0.4 0.5 0.5 0.6 2.0

Sum of Spall, SoftParticles, Clay balls 1.4 2.5 2.6 1.3 2.4 3.0 3.4 1.3 0.9 0.7 3.5

Flat and Elongated 0.0 0.3 4.2 1.8 0.0 2.5 3.3 1.0 1.2 6.1

Lightweight Particles 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.5

Specific Gravity

Bulk Oven Dry 2.636 2.614 2.629 2.609 2.653 2.605 3.369 2.630 2.641 2.564

Bulk Saturated Surface Dry 2.658 2.650 2.665 2.642 2.688 2.642 3.542 2.646 2.660 2.621

Apparent Oven Dry 2.695 2.711 2.729 2.696 2.750 2.705 4.063 2.676 2.691 2.719

Absorption 0.83 1.36 1.41 1.24 1.34 1.42 5.06 .067 0.70 2.23 1.7

*I.O. Was tested as glacial overburden. Sample is actually mixed-sized rock.

Table 4. Composite 2 results for testing glacial overburden material type.

Composites 2 ZZ7 ZZ8 ZZ9 Specs

Los Angeles Abrasion 24.5 22.7 19.9 40

Magnesium Sulfate 6.1 12.0 3.5 12

Cretaceous Ore- • Gradations: Some gradations fall within Class 5.• Absorption: There is only one composite from which to make observations. However,

this result indicates the material is very absorptive (Table 5).• Specific Gravity: Is relatively higher than for glacial overburden. This is due to the

presence of iron.• Clay Lumps: Contains a significant amount of clay balls and lumps.• Soundness (Magnesium Sulfate): Does not pass specifications since the composite

broke down 71.5% of its weight by volume (Table 6).• Field Observations: There are very few stockpiles of this material and they are located

within the Calumet study area.

Table 5. Composite 1 results for testingCretaceous ore material type.

Composite 1 B9 Spec

Clay Balls & Lumps 10.2 0.3

Specific Gravity

Bulk Oven Dry 2.799

Bulk Saturated Surface Dry 3.023

Apparent Oven Dry 3.565

Absorption 7.67 1.7

Table 6. Composite 2 results for testingCretaceous ore material type.

Composites 2 ZZ3 Spec

Los Angeles Abrasion NA 40

Magnesium Sulfate 71.5 12

Natural Ore Coarse Tailings-• Gradations: The gradations may make Class 5, but can contain excess coarse rock.

The coarse fraction of the stockpile may have other valuable aggregate applicationsother than Class 5.

• Absorption: Material is very absorptive, which may affect the performance of thismaterial type as an aggregate (Table 7).

• Specific Gravity: Is slightly higher due to the higher density of iron.• Clay Lumps: Meets specifications.• Soundness (Magnesium Sulfate): The material does not meet specifications (Table 8).• Abrasion: The material does not meet specifications for abrasion.• Field Observation: The piles contain sorted, pre-crushed rocks and are near major

highways.

Table 7. Composite 1 results for testing natural ore coarse tailings material type.

Composite 1 A1 A2 A3 A4 A5 A6 A7 A8 Spec

Tests ZZ1 ZZ2

Clay Balls & Lumps 0.62 0.62 0.39 0.39 0.43 0.43 1.08 1.0 2.0

Flat and Elongated 0.0 1.9 0.0 0.0 0.7 1.8 0.0 1.4

Specific Gravity

Bulk Oven Dry 2.794 2.648 2.748 2.887 2.817 2.690 2.971 2.564

Bulk Saturated Surface Dry 2.940 2.812 2.904 2.977 3.023 2.825 3.134 2.719

Apparent Oven Dry 3.263 3.169 3.257 3.172 3.552 3.113 3.507 3.005

Absorption 5.13 6.19 5.70 3.12 7.35 5.06 5.14 6.02 1.7

Table 8. Composite 2 results for testing natural ore coarse tailings material type.Composites 2 ZZ1 ZZ2 Spec

Los Angeles Abrasion 45.3 46.5 40

Magnesium Sulfate 33.8 29.3 12

Natural Ore Fine Tailings-• Gradations: The gradations are too fine to meet Class 5 specifications, however it

may fall within the specifications of other construction Classes. • Absorption: Material is very absorptive of water, which may affect the performance of

this material type as an aggregate (Table 9).• Specific Gravity: Is slightly higher due to the higher iron content and is variable. This

is likely due to the presence of both cherty and iron-bearing rock particles.• Fine Aggregate Angularity: Between 50 and 60 percent of the rock particles are

considered to have angular “edges” (Table 10).• Field Observations: This material is very well sorted because it was transported and

deposited into basins filled with water. The fine tailings are graded by size within abasin.

Table 9. Composite 1 results for testing natural ore fine tailings material type.

Composite 1 C10 C11 C12 C14 C15 C16 C17 C18 C19 Spec

Tests ZZ4 ZZ5 ZZ6

Clay Balls & Lumps 0.31 0.31 0.40 0.40 0.32 0.00 0.80 0.00 0.00 2.0

Specific Gravity (Fine)

Bulk Oven Dry 3.695 3.623 3.660 3.268 3.137 3.170 3.312 3.195 2.894

Bulk Saturated Surface Dry 3.773 3.680 3.715 3.326 3.197 3.234 3.409 3.292 2.957

Apparent Oven Dry 4.007 3.844 3.873 3.469 3.339 3.385 3.667 3.539 3.090

Absorption- 2.10 1.59 1.50 1.77 1.93 2.00 2.92 3.05 2.18 1.7

Table 10. Composite 2 results for testing natural ore fine tailings material type.Composites 2 ZZ4 ZZ5 ZZ6

Fine Aggregate Angularity 59.3 56.1 55.3

Mixed-Sized Rock (Taconite and Natural Ore)-• Gradations: The gradations will vary considerably with this material because the

stockpiles are unsorted. The results over-represent the particles that are smaller than acobble, due to the sampling methodology. Some parts of the pile may need to becrushed.

• Absorption: Material is very absorptive of water, which may affect the performance ofthis material type as an aggregate (Table 11). The sample D26 was tested with theglacial overburden samples, but originates from a mixed-sized rock stockpile. It wasincluded in these results to give further qualitative data about mixed-sized rockmaterial type.

• Specific Gravity: Is slightly higher due to the higher density of iron and is variable. This may be due to the presence of both cherty and iron-bearing rock particles.

• Soundness (Magnesium Sulfate): The material does not meet specifications forsoundness (Table 12).

• Field Observations: The difference between the “natural ore” and “taconite” aredifficult to discern in the field. There are different rock types observed within thesepiles (i.e., paint rock and glacial boulders).

Table 11. Composite 1 results for mixed-sized rock (natural ore and taconite) material type.

Composite 1 E30 E31 E32 D26 Spec

Tests ZZ10

Clay Balls & Lumps 0.80 0.80 0.81 0.40 2.0

Flat and Elongated 4.3 4.2 8.6 3.3

Specific Gravity

Bulk Oven Dry 2.827 3.321 3.475 3.369

Bulk Saturated Surface Dry 3.009 3.431 3.593 3.542

Apparent Oven Dry 3.454 3.726 3.946 4.063

Absorption- 6.42 3.28 3.44 5.06 1.7

Table 12. Composite 2 results for mixed-sized rock (natural ore and taconite) material type.

Composites 2 ZZ10 Spec

Magnesium Sulfate 26.2 12.0

Specific Gravity (bulk oven dry)The graph shown in Figure 8 shows the range of values for the “bulk oven dry” specific gravityresults. The results are graphed in a “box and whisker” plot. Out of all the material types, glacialoverburden yielded the most consistent results showing a small range of values. Coarse tailingsalso are relatively consistent. Fine tailings and mixed-rock (includes natural ore and taconite) have a large range of values for specific gravity. The implication of these results suggest thatthese materials have varying rock mineralogy. For fine tailings, the specific gravity results mayshow the varying amount of hematite and chert.

Both the fine portion and coarse portion of the samples were tested for specific gravity for allsamples with the exception of fine tailings. (Because of the fine particle size, only the finespecific gravity test was requested). The results are the composite of the fine and coarse testresults.

Specific Gravity by Material Type

Coarse T

ails

Cretaceo

us

Fine Tails

Mixed-Rock

Overburden

Material Type

2.5

3.0

3.5

4.0

Spec

ific

Gra

v ity

(bul

k o v

en d

ry)

Figure 8. A “box and whisker” plot of specific gravity. The line in the box represent the median value. The boxindicates the 1st standard deviation. The vertical lines represent the range of values. The star represents an outlier.

Absorption by Material Type

Coarse T

ails

Cretaceo

us

Fine Tails

Mixed-Rock

Overburden

Material Type

0

1

2

3

4

5

6

7

8

Abs

orpt

ion

Figure 9. A “box and whisker” plot of absorption. The line in the box shows the medianvalue. The box indicates the 1st standard deviation. The vertical lines represent the rangeof values. The stars represent outliers.

AbsorptionAbsorption measures the amount of water soaked into the small pores and fractures on a rocksurface. Out of all the materials, overburden is the least absorptive (Figure 9). Fine tailings isalso a relatively non-absorbent material and has the narrowest range of results. Cretaceous oreand coarse tailings have the highest values for absorption. These results are consistent with fieldobservations. Cretaceous ore consists of moderately cemented rocks that contain smaller rocks.The cement of this conglomerate has a porous texture. The cherty rocks that comprise coarsetailing piles are also very porous.

Soundness Results (Magnesium Sulfate)

33.829.3

71.5

6.112.0

3.5

26.2

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

Com

posi

te L

oss

Coarse Tailing Cretaceous Ore Glacial Overburden Mixed Rock

Figure 10. Soundness by material type.

SoundnessThe soundness test uses magnesium sulfate to re-create freeze/thaw processes. The more amaterial breaks down due to freezing and thawing, the higher the potential that the material willperform poorly as a construction material. This test was performed on the second level ofcomposites (the composites of composites). Therefore, one soundness result comes from thecombination of 15 or less samples.

Four material types were tested: coarse tailings, cretaceous ore, glacial overburden, and mixed-sized rock. The maximum value set by MNDOT for construction aggregate for concrete andbituminous material is 12.0. Only glacial overburden passes this specification (Figure 10). Oneof the three glacial overburden values reaches the maximum limit of the specification. Thisresult is upwardly skewed because of the inclusion of mixed-sized rock with that particularcomposite. Both natural ore and mixed-sized rock exceed the specification. Cretaceous oregreatly exceeds the specification with the value of 71.5% loss.

GradationsFive charts with examples of the various material types vs. Class 5 specifications are presented(Figure 11). All but 2 of the 82 samples were sieved and the results are listed in Appendix D. Inthe examples below, the results are shown in comparison with Class 5 specifications. Thiscomparison is used because Class 5 has many construction applications. The results indicateglacial overburden piles contain an abundant amount of fines and may need to be mixed withcoarser material to make Class 5. Coarse tailings tend to contain larger rock sizes. Fine tailingscontain too many fines to be used in Class 5; however, they may fit in the gradations specified for another material class. For mixed-size rock, the gradations indicate that it could pass Class 5specifications; however, the sample under-represents the large particle size within the stockpile. Cretaceous ore may fall within Class 5 gradations; however other aggregate tests show this to bea substandard construction material.

Iron Ore ResultsThe results for the iron ore testing are listed in a tabular format in Appendix E. The results canalso be viewed in the database. Iron ore testing included chemical assays of the eight mostcommon oxides. The percent hematite was calculated using this conversion:

(Fe - Fe++) x 1.4297 = Hematite

The iron oxide results were calculated using this conversion:

Fe++ x 1.2870 = FeO

If so desired, the other mineralogy can be determined from these assays. The samples arerandom grab samples and do not represent the average iron percent for the total stockpile.

E x a m p l e s o f M i x e d - S i z e d R o c k v s. C l a ss 5

0

20

40

60

80

100

1 3/ 4 3/ 8 #4 #10 #40 #200

Si e v e Si z e s

M NDOT M ax MNDOT Mi n

M i xed-Si zed Rock Sampl e 32 Mi xed-Si zed Rock Sampl e 74

Ex a m pl e s o f Ov e r b ur d e n Gr a d a t i on s v s. C l a ss 5

0

20

40

60

80

100

1 3/ 4 3/ 8 #4 #10 #40 #200Si e v e Si z e s

M NDOT M ax M NDOT M i n

Gl ac i al Over bur den Sampl e 7 Gl ac i al Over bur den Sampl e 70

E x a m p l e s o f C r e t a c o u s O r e v s . C l a s s 5

0

2 0

4 0

6 0

8 0

1 0 0

1 3 / 4 3 / 8 # 4 # 1 0 # 4 0 # 2 0 0

S i e v e S i z e s

M N D O T M a x M N D O T M i n

C r e t a c e o u s O r e Sa m p l e 1 7 C r e t a c e o u s O r e Sa mp l e 2 2

E x a mp l e s o f F i n e T a i l i n g s v s . C l a s s 5

0

2 0

4 0

6 0

8 0

10 0

1 3 / 4 3 / 8 # 4 # 1 0 # 40 #2 0 0

S i e v e S i z e

M N D O T M a x M N D O T M i n

Fi n e T a i l i n g s Sa mp l e 77 Fi n e T a i l i n g s Sa mp l e 5 9

E xa mpl e s of C oar se T a i l i ngs vs . C l as s 5

0

20

40

60

80

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1 3/ 4 3/ 8 #4 #10 #40 #200

S i e v e S i z e s

M NDOT M ax M NDOT M i n

Coar se T ai l i ngs Sampl e 18 Coar se T ai l i ngs Sampl e 55

Figure 11. Examples of gradation results

C. DATABASE RESULTSFrom the initial database modeling, about 95% of the data and relationships were designed andcaptured. The database consists of many related tables and forms for browsing the information. Other tables and queries were created for the purposes of mapping and error checking. Thoughinformation about stockpile composition, sample results, and other data can be browsed usingexisting forms and queries, a familiarity with database design and programming concepts isnecessary to develop other products.

The links or relationships between the main tables in the database may be viewed withinMicrosoft Access using the Tools, Relationships function. A view of the relationships may beseen in Appendix B (Physical Data Model). While most of the data relationships can be seen inthe database, other relationships, such as stockpile ownership versus surface and mineralownership, must use Geographic Information Systems (GIS) software for viewing.

For the stockpiles, the database needs to be used in conjunction with Plates III and IV. Thestockpile identification (ID) numbers correspond between the plates and the database. Thestockpiles found in Virginia have ID numbers ranging from 101 to 198. The stockpiles withinthe Calumet site have ID numbers ranging from 301 to 434. The entire database is included onthe CD-ROM that is part of this report. The CD-ROM also contains ArcView shapefiles of thestockpile footprint, vegetation cover types, and the mining roads. Copies of associated metadatafor both the shapefiles and database tables are included in both PDF and HTML formats. Thereport is in both WordPerfect 9 and PDF formats. The plates are available in EPS and PDFformats.

D. STOCKPILE ACCESSPlates III and IV summarize stockpile access within the Calumet and Virginia study areas. Thetwo access issues mapped for this project were vegetation cover type on each stockpile andtransportation to stockpiles.

VegetationThe vegetation coverage was limited to areas delineated as stockpiles. The major forestvegetation types found in the two study areas were aspen-birch and conifers. The mapping unitssummarizing the vegetation are based upon these forest types and their merchantability. Fivemapping units were created for vegetation:

Aspen-Birch, 1-5 inch dbh: aspen-birch is the major species of the forest canopy, withover 50% canopy cover. A majority of the trees have a diameter at breast height (dbh)over 1 inch, but less than 5 inches. Trees this size are generally considered non-merchantable.

Aspen-Birch, >5 inch dbh: aspen-birch is the major species of the forest canopy, withover 50% canopy cover. A majority of the trees have a diameter at breast height (dbh)over 5 inches. Trees this size may be merchantable.

Conifer, 1-5 inch dbh: conifers are the major species of the forest canopy, with over 50%canopy cover. A majority of the trees have a diameter at breast height (dbh) over 1inch, but less than 5 inches. Trees this size are generally considered non-merchantable.

Conifer, >5 inch dbh: conifers are the major species of the forest canopy, with over 50% canopy cover. A majority of the trees have a diameter at breast height (dbh) over 5inches. Trees this size may be merchantable.

Open: areas that are barren, contain open water, grassland, shrubs, or are treereproduction areas. Tree reproduction areas are those areas containing trees with adiameter at breast height of less than 1 inch. This category also includes any forestcanopy with less than 50% cover.

TransportationTransportation infrastructure within the two study areas included major roads and railroadgrades, and private mining roads and old railroad grades. Coverages of major roads and railroadgrades were obtained from the Minnesota Department of Transportation. Private mining roadsand old railroad grades were digitized and classified according to information gathered by fieldchecks. Berms or washouts were not mapped. Mapping units were created to summarize thecondition of private mining roads found in the study areas and if the road is a former railroadgrade. A private mining road in “good to moderate condition” is easily accessible and needslittle modification. Private mining roads in “poor to moderate condition” may need to be re-graded, widened, or have other modifications.

The classification of the roads is based upon information gathered during the summer of 2000. Road conditions change over time and field checks may be necessary to verify a particular road’scondition. Private mining roads are not open to public transportation. The surface owner is to becontacted for permission to use any private road.

V. STOCKPILE USESPart of the purpose for gathering data about stockpiles was to determine their potential uses. Specifically, the stockpiles were to be examined for use in the aggregate industry and iron miningindustry. This was accomplished by:

• examining current use of mine waste material• examining past use of stockpile material• gathering historical information about iron content from mining companies• classifying stockpile material types• quantifying aggregate material types through sampling• characterizing material as it was seen in the field.

There is a current demand and usage of mine waste material. As of the fall of 1998, four miningcompanies have approval from MNDOT to use their taconite tailings in bituminous mixtures(personal communication, John Garrity, MNDOT). Unique specifications for taconite in

mixtures include a maximum limit on specific gravity and geographical restriction. In addition totaconite tailings, glacial overburden is processed as it is stripped off the iron formation.Processing from old stripping stockpiles also occurs. The State also has leases with aggregateand logging companies for mining natural ore coarse tailings stockpiles. These coarse tailingsare currently being used for road base, logging roads, fill, and pipelines.

The process of re-using iron stockpiles is not new to the Range. In the past, old natural ore pilesand tailing basins have been reprocessed for iron ore with the introduction of new processingtechnologies. This has occurred within the Calumet study area. The coarser particles from basin431 were excavated and processed for iron in the late 1950's.

The first step to determine usage of iron stockpiles is to examine methodologies conducted in thepast to locate the iron-rich piles. First, the location of these piles were identified throughstockpile records or anecdotal knowledge by the people who built these piles. Then, the miningcompanies performed site-specific evaluations to determine the economic return for setting up aprocessing plant. The first part of this methodology, identification of potential stockpiles throughhistorical research, has been accomplished by gathering and organizing stockpile informationwithin the two study areas. Out of all the iron ore stockpiles, approximately 43% of the themcontain some iron information.

The classification of stockpile material type has the greatest implication for usage. Generalizations based upon quantitative and qualitative data can be made about each materialtype. The quantitative data are derived from the sample analysis; the qualitative data are derivedfrom field observations. Listed below are some potential uses for stockpile material types. Thislist is a guide to help determine which material type is most likely to suit some commonly knowndemands (i.e., fill, Class 5, railroad ballast, etc.). This list is not intended to exclude a materialtype from being used for other applications.

Glacial Overburden High Aggregate Potential*

• Good source of glacial boulders-To be used as landscaping rocks-To be crushed for aggregate material-To be used as rip-rap

• Good source for fill• Can be screened to make class 5• Screened fines can be used as a binder• Market already exists for this material type • Has consistent specific gravity and absorption test results for both study

areas• Meets most specifications for concrete and bituminous mixtures

Low Iron Potential• Little to no iron is present in this material type

*Glacial overburden stockpiles do not degrade as it is being piled. This is the most abundant materialtype and one of the best sources of aggregate. In addition, steeply sloped, open-pit mine walls can beeasily reclaimed by allowing aggregate contractors to mine the material exposed along the upper half ofthe mine wall.

Natural Ore Coarse TailingsHigh to Moderate Aggregate Potential

• Material is has been pre-crushed and pre-sorted• Could be screened to meet Class 5 specifications• Could be used for fill and potentially in bituminous mixtures• Markets already exist for this material type• Material did not perform well in laboratory tests

Low to Moderate Iron Ore Potential• Piles generally contain between 20 and 30 percent iron. This information is

derived from known iron ore contents

Natural and TaconiteMixed-Sized Rock

Moderate Aggregate Potential• Material could meet Class 5 specification with screening and washing• Could be used for fill and road base• Out of all the stockpile types, the material has the largest variation between

stockpiles• Material did not perform well in laboratory tests• Leaves a red residue and can stain

Unknown Iron Potential• Cannot generalize iron potential for this material type due to the large

variation

Taconite Rock BouldersModerate Aggregate Potential

• Material is a good source for rip rap• This material was not tested in the laboratory. Could not sample in the field

due to the large size of boulders• Boulder size makes the material more difficult to handle• Could potentially be a source for crushed rock; but the hardness of this rock

type may wear on crushing machinesModerate Iron Potential

• Older piles may contain a high taconite content

Natural Ore Fine TailingsModerate Aggregate Potential

• A source of finely crushed rock that is very well sorted• Sand may be used as iron source for bituminous mixtures• Clay particles are source of pigments for bricks and other specialty needs• Performed moderately in laboratory tests

Moderate Iron Potential• Has been mined in the past for iron within the study area

Cretaceous OreLimited Aggregate Potential

• Performed very poorly in laboratory testsHigh to Moderate Iron Potential

• Stockpiles is comprised of 40 to 50% iron ore

Cretaceous OverburdenLimited Aggregate Potential

• Piles contain may contain a variety of material types including paint rockand glacial overburden

• Only one gradation sample was takenModerate Iron Potential

• Iron percentages are in the mid-forties

SlateLimited Aggregate Potential

• Is considered substandard rock for use in construction material• However, may be used as decorative rock (i.e., flagstone)

Limited Iron Potential• Contains mostly silica minerals

Paint RockLimited Iron Potential

• Is considered substandard rock for use in construction material• The powdery texture may be a source for pigment

Limited Iron Potential• Iron has been partially leached out of rock as it was altered; however, the

rock as a higher Aluminum Oxide content

Ownership ReferencesItasca County Recorder/Registrar of Titles Office.

St. Louis County Recorder/Registrar of Titles Office.

Consolidated Title and Abstract Company (Duluth, MN).

Great Northern Iron Ore Properties, December 1995, Lean Ore and Tailings Booklet.

U.S. Steel Group - Northern Lands and Minerals, Rouchleau Area stockpile information and 1982 USX plates.

Minnesota Department of Natural Resources, 1999, Division of Lands and Minerals,Annual Operations Report and State Stockpile Map Supplement.

Minnesota Department of Natural Resources, May 1998, Division of Minerals, StockpileReport to St. Louis and Itasca Counties.

Minnesota Department of Natural Resources, January 1986, Division of Minerals,Minnesota Mesabi Range Maps.

Aggregate ReferencesAggregate Resources Task Force: Final Report to the Minnesota Legislature, 2000.

Lean Ore and Tailings Booklet, 1995, Great Northern Iron Ore Properties, Map 3 andMap 17.

Maps of the Mesabi Range, 1982, United Steel Corporation, Plates 5, 6, 24, and 25.

Mesabi Range Maps, 1959, Great Northern Iron Ore Properties.

Mesabi Range Maps, 1955, Great Northern Iron Ore Properties.

Minnesota Department of Natural Resources, 1999, Division of Lands and Minerals,Annual Operations Report and State Stockpile Map Supplement.

MNDOT, 1995, Standard Specifications for Construction, Minnesota Department ofTransportation, pp. 695-721.

MNDOT, 1998, Aggregate Production I Handbook, Minnesota Department ofTransportation, pp. 5.1 - 5.74.

APPENDIX A

Explanation of Aggregate Tests Map of Sample Locations

Explanation of Aggregate Tests

Specific Gravity and Absorption (Fine and Coarse Aggregate): Specific gravity is the measure of weight divided by volume. These numbers help engineers andcontractors design concrete and bituminous mixes. It is done on fine particles (less than 4.75mm) and coarse particles (equal to or greater than 4.75 mm). Absorption measures the porositywhich is the amount of water a material absorbs. This basic test was performed on all materialtypes and composites (A1 though E32).

Flatness and Elongated: This is the measure of rock particles to determine what percent of the material has a flat andelongated shape. This test determines the amount of deleterious particles, like shale and slate,that are in a construction material. The following material types were tested: Coarse Tailings,Glacial Overburden, and Mixed-Sized Rock (A1-A8, D20-D29, and E30-E32).

Clay Lumps: Clay lumps sometime occur in material that has abundant silt and clay size particles. Clay lumpsare easily broken down and are considered deleterious in concrete and bituminous mixtures. Thistest was performed on all material types (A1-E32).

Fine Aggregate Particles: This test measures the angularity of fine rock particles. This test was only performed on FineTailings composites (C10-C19).

Lightweight Particles and Spall: A lightweight particle test is used to determine the amount of argillite and shale in a givenmaterial. These are considered to be harmful rocks in mixtures because of their ability to absorbwater. The crystal/mineral alignments cause planes of weakness as the particles break down dueto freeze and thaw. Spall is a general term applied to all rock particles that are considereddeleterious to mix designs. These two tests were performed only on Glacial Overburdencomposites (D20-D29).

Abrasion and Soundness:Abrasion is a predictive test to determine how well a material can withstand “handling.” Because materials break down into smaller particles as they are being scooped, dumped, andtransported, this test attempts to measure the potential breakage. Soundness is a chemical test todetermine how well a material can withstand freezing and thawing. These tests were performedon composites (ZZ1-ZZ3, and ZZ7-ZZ10).

23 Sample Locations#

Study Area

Stockpile

Pit

#

####

#

###

#

##

#

# #

1

2345

67

89

10

1112

13

1415

Virginia Sample Locations

0.5 0 0.5 1 1.5 Miles

APPENDIX B

Business Object ModelConceptual/Logical Data Model

Physical Data Model

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APPENDIX C

Project Definition

1

Project Definition:Focus Statement and Information Needs

for LCMR Stockpiles project

Attendees:Heather Anderson (HA)Steve Dewar (SD)Vicki Hubred (VH)Dennis Martin (DM)

Facilitator/Modeler:Jill Bornes

Coach/Recording Analyst:Renee Johnson

Focus Statement for Project:

1) Breadth: Create an information gathering tool that deals with stockpile information for thetwo defined study areas (known as Calumet and Virginia) on the Mesabi Iron Range. Morespecifically, this data is being compiled and related to help discover alternative uses for stockpilematerial. “Clearinghouse of information”–I.e., We (the state and other fee owners) will belooked at to provide this information to clients, that is, to provide a service of interpreting theinformation that is being collected as part of this project.

From...When the material was taken out of the ground (for geology, mineral and miningpurposes) or a snapshot of what is happening now, in the year 2000 (for ownership andvegetation purposes).

To...When project is completed in June 2001. The database will not bemaintained/updated after the project end date.

Including: Surface, mineral and material ownership, location of stockpile, also locationrelative to a road, vegetation on the stockpile, description of material type at surface ofstockpile, samples taken at stockpiles (includes overburden, rock and tailing basins),references to historical information (this includes reports and other sources containinginformation about material types, iron content, silica content, tonnages, etc.), and basicbroad information from fee owners.

Excluding: DNR environmental review process (archaeology, grape fern, merchantabletimber (forestry)), chain of title for material, surface or minerals, granting access rights(easements, trespass restrictions), location of berms, fences or gates, iron ore reserves andin situ bedrock and blasted material.

2

2) Emphasized Perspective: DNR Lands & Minerals Division, disciplines include: attorneys,geologists, engineers, etc., other fee owners (e.g., US Steel), Counties (St. Louis and Itasca). NotJoe Public.

3) Depth: Full detail model

4) Universality: How flexible? How specific or generic?We want to be able to account for other issues, such as ownership and sampling that mayappear outside of our study areas (since we are a pilot project). For example, if a tailingsbasin is drilled, we need flexibility to account for other sampling information and perhapsother historical information.

Geopolitical: Mesabi Iron Range in Minnesota

Time: Hard to guess? Depends on future requests from division director and others. Thedatabase will not be maintained/updated after the project end date.

5) Scope of Integration:DNR’s Division of Forestry--Forest inventory, other DNR reviews/uses like Wildlife, EcoServices, etc. Permit to Mine review (only for material being used for iron units), futuremine plans in adjacent areas, forecasting (e.g., MIS-Minnesota Iron & Steel), M Permitand M Lease database in Lands & Minerals.

3

Information NeedsQuestions to be answered with the results of this project in/out(In focus-should be part of project, Out focus-beyond the project scope) person Focus

1)

2)

3)

4)

5)

6)

7)

8)

9)

10)

11)

12)

13)

Where is the nearest overburden stockpile in relation to constructionsite?

Where is stockpile with base coarse aggregate, Class 5 aggregate, and/orconcrete aggregate, in relation to construction site? (Aggregate classesare too specific compared to the information that is being collected, wewill be able to provide a more general answer to this question.)

For ‘X’ stockpile at ‘Y’ location, who do I have to talk to in order to usethis pile? (question may be asked by DNR or Agg. Operator)

Any materials to use as road fill within “reasonable” haul distance ofhighway 169 at Pengilly?

How may yards available(volume) for construction project?

Has stockpile been previously sampled [in the past], if so, what are thespecs? (Results?)

For “Bovey beautification project”, which property contains 1000 glacialboulders for landscaping? Want to buy them, money is no object. (Willprobably be able to provide general info. by material type, like‘boulders’, and we can hint where good sources may be, but not specificinfo like 1000 glacial boulders.)

For ‘X’ property (by common name or legal desc.), who owns theproperty and what is stockpiled there?

What is access like to the stockpile? Does road exist? What type? Improvements needed? (We nixed the idea that we could capture or careabout if improvements were needed--per the focus statement.)

M.I.S. needs 5 m. tons of low grade iron ore (<40% total iron), how closeto the proposed M.I.S. plant? (Some of this information will be includedwhen available)

Which stockpiles contain material suitable for aggregate?

For coloring bricks, need red pigment (red ore tailings), Where? Whoowns it? Who do I talk to?

Is stockpile covered with trees? Do we need to clear cut?

HA

DM

VH

SD

SD

HA

DM

VH

HA

DM

VH

SD

HA

IN

IN

IN

IN

IN

IN

IN

IN

IN

IN

IN

IN

IN

4

14)

15)

16)

17)

18)

19)

20)

21)

22)

23)

24)

25)

26)

27)

Animal farm needs an area with no vegetation, can I lease this area fromyou? (Key is non-material use of the property)

Company wants to use aggregate. What does the company need to do? Will the company need to do reclamation?

Railroad needs rock of certain hardness and maybe certain size to crunchup and make into ballast. (Maybe rock type can indicate this)

Is stockpile in a park or other possible restricted area, how many hoopsto jump thru? (‘in the park’ is IN, but ‘hoops to jump thru’ is OUT.)

Why isn’t there more information about an area or stockpile? (Assuminga gap exists in the information for certain attributes in the system) (Anexplanation for this inconsistency will be included in the metadata.)

Are there other owners to talk to about trespass issues?

Do you have pictures of the stockpiles ‘A’, ‘B’, or ‘C’?

How many different owners are involved in this stockpile(commingling)?

I’m a student, I want all of your information. (Public information)

Calumet Ski Hill–want to make stockpile into a ski hill. How much willit cost to purchase? (Appraisal)

Has this stockpile been previously used for aggregate? From where onthe stockpile has material been removed? (MNDNR M lease/M permitsmay contain information about which stockpile is used, but not whichpart of the stockpile material is removed from. M permits and leases arepart of the scope of integration.)

If material (from item #24) has been used, by whom?

Where was this material (from item #24) used?

Where are all stockpiles on the Range that have been used for aggregate?(It was decided that our answer to this inquiry could be ‘No, we cannoteasily provide that information range wide’, or maybe this would be anintegration with the M lease/M permit database to provide a partialanswer. This project only covers two study areas, perhaps the newmining features coverage could be used to find ALL stockpiles?)

DM

RJ

SD

HA

HA

HA

DM

HA

RJ

DM

HASD

“

“

SD

IN

OUT

IN

IN

IN

IN

IN

IN

IN

OUT

OUT

OUT

OUT

OUT

APPENDIX D

Sieve Results

Gradation T

est Results

Sample

Num

berStockpile ID

43

2.52

1.51.25

13/4

5/81/2

3/84

810

1630

4050

100

1154

100100

100100

9998

9794

9288

7851

4847

4133

2822

11

2130

100100

100100

9996

9493

9190

8884

8079

7464

5849

29

3130

100100

100100

9999

9897

9694

9287

8382

7663

5345

27

4130

100100

100100

10098

9795

9493

9184

8180

7463

5648

30

5130

100100

100100

9593

9291

8886

8478

7472

6960

5345

28

6168

100100

10092

9291

9088

8785

8476

7473

6955

4637

22

7168

100100

100100

10099

9898

9897

9693

8988

8576

6960

36

8168

100100

10096

9594

9392

9087

8682

7878

7361

5446

30

9168

100100

100100

10099

9896

9593

9189

8887

8268

6154

38

10107

100100

100100

9893

9290

8885

8372

6765

5343

3937

33

110

100100

100100

8678

6960

5551

4739

3635

3024

2017

10

120

100100

9796

8679

7671

6866

6359

5755

5042

3631

19

130

100100

100100

9999

9998

9898

9797

8681

6546

3625

11

14174

100100

10083

6966

5948

4538

3319

1413

108

76

4

15174

100100

10092

7065

6056

5247

4127

1917

118

76

4

16338

100100

10098

9593

8983

8076

6956

5148

4132

2722

14

17373

9191

9178

7268

6358

5552

4943

4039

3430

2813

3

18353

100100

100100

100100

9894

8863

4828

2018

115

21

0

19362

100100

10098

9591

8470

6348

3619

1211

86

43

2

20362

100100

10099

9796

9489

8568

5724

2221

166

21

0

21362

100100

10097

8883

7771

6764

6052

5049

4636

2720

8

22361

100100

10097

9593

9289

8682

7866

6361

5649

4540

19

23336

100100

100100

9995

9188

8682

7868

6664

6055

5250

31

24302

100100

100100

100100

100100

100100

100100

9998

9482

7156

26

Page 1 of 4

Sample

Num

berStockpile ID

43

2.52

1.51.25

13/4

5/81/2

3/84

810

1630

4050

100

25302

100100

100100

100100

100100

100100

10099

9289

8470

5541

20

26302

100100

100100

100100

100100

100100

100100

9999

9687

7354

24

27313

100100

100100

9999

9584

7872

6541

2521

126

33

2

28305

100100

9393

9189

8885

8482

7972

6968

6143

3121

8

29335

100100

100100

100100

100100

100100

100100

9897

9492

9191

89

30335

100100

100100

100100

100100

100100

100100

100100

10099

9997

72

31335

100100

100100

100100

100100

100100

100100

10099

9796

9695

89

32339

100100

10097

9391

8984

8177

7161

5756

5245

3934

25

33353

100100

10098

9894

9187

8582

7867

5552

3922

149

4

34353

100100

100100

9795

9392

9087

8475

7271

6245

3425

12

35432

100100

100100

100100

100100

100100

100100

100100

10099

9792

67

36432

100100

100100

100100

100100

100100

100100

100100

9890

7556

27

37432

100100

100100

100100

100100

100100

100100

100100

10097

8867

26

38432

100100

100100

100100

100100

100100

100100

100100

9990

7148

18

39429

9090

8580

6861

5134

2615

82

11

11

00

0

40429

100100

9893

8380

7573

7169

6448

4038

3325

1916

11

41429

100100

9896

9090

8886

8380

7241

3432

2617

129

5

42429

10092

9076

5749

4237

3533

3023

2019

1613

1110

8

43424

100100

100100

100100

100100

10098

6327

2017

139

76

4

44424

100100

100100

100100

100100

100100

9658

4845

3725

1915

11

47434

100100

100100

100100

100100

100100

100100

9999

9672

5644

30

48434

100100

100100

100100

100100

100100

100100

10092

6755

4633

17

49419

100100

100100

9898

9487

8376

6352

3126

1815

1413

11

50419

100100

100100

10097

9490

8680

6935

2624

1814

1312

10

51419

100100

100100

9998

9592

8882

7128

2019

1614

1312

10

52419

100100

100100

9482

6758

5350

4410

11

11

00

0

Page 2 of 4

Sample

Num

berStockpile ID

43

2.52

1.51.25

13/4

5/81/2

3/84

810

1630

4050

100

53418

100100

10098

9693

9085

8178

6837

3230

2416

1310

7

54418

100100

8776

6964

5652

4945

4026

2019

1611

75

3

55418

100100

9794

9290

8989

8885

8274

5450

3822

1511

7

56418

100100

10097

9696

9593

9290

8769

6058

4934

2519

13

57418

100100

100100

9896

9591

8985

7546

3635

2921

1715

11

58340

100100

100100

100100

100100

100100

100100

100100

9995

8466

24

59340

100100

100100

100100

100100

100100

100100

9999

9791

8370

35

60340

100100

100100

100100

100100

100100

100100

100100

10094

8470

33

61327

100100

100100

100100

100100

100100

100100

9897

9793

8877

41

62327

100100

100100

100100

100100

100100

100100

9999

9894

8880

48

63327

100100

100100

100100

100100

100100

100100

100100

9995

8979

42

64325

100100

100100

100100

100100

100100

100100

100100

9995

8877

38

65325

100100

100100

100100

100100

100100

100100

9998

9794

8876

34

66360

100100

10097

9695

9392

9190

8767

6158

4016

84

1

67372

100100

10097

9796

9493

9291

8983

7674

6035

2415

4

68369

100100

100100

10099

9894

9285

7867

6564

6143

3119

9

69374

100100

100100

9897

9384

8175

6541

3837

3529

2419

11

70409

100100

10097

9795

9390

8885

8273

6462

4724

158

2

71409

100100

10099

9796

9290

8886

8274

6967

5224

125

1

72409

100100

10098

9695

9493

9290

8985

7876

6132

1910

3

73409

10093

9393

9393

9392

9292

9190

8888

7957

4128

8

74411

100100

10097

9493

9187

8374

6654

4947

4237

3331

25

75402

100100

10097

9695

9392

9190

8985

8282

7452

3927

12

76423

100100

100100

100100

100100

100100

100100

10099

9996

9072

27

77423

100100

100100

100100

100100

100100

100100

100100

9998

9480

31

78423

100100

100100

100100

100100

100100

100100

100100

10096

9076

33

Page 3 of 4

Sample

Num

berStockpile ID

43

2.52

1.51.25

13/4

5/81/2

3/84

810

1630

4050

100

79430

100100

10098

9795

8662

5035

2312

1010

98

76

5

80430

100100

100100

9287

8071

6557

4717

1110

98

87

6

81396

100100

100100

100100

100100

100100

100100

100100

9999

9894

56

82340

100100

100100

100100

100100

100100

100100

100100

9994

8367

27

Page 4 of 4

APPENDIX E

Iron Ore Testing Results

Iron Ore C

hemical A

ssay Results

Sample N

umber

Fe

Hem

atiteF

e++F

eOSiO

2A

L2O

3C

aOM

gON

a2OK

2OM

nOF

reeSiO2

CO

2

1441.91

59.380.38

0.4930.58

2.2000.079

0.0570.023

0.0530.869

26.690.06

1537.85

52.690.98

1.2640.14

1.0880.036

0.0560.010

0.0290.355

37.100.07

1629.94

41.430.98

1.2648.30

6.4260.760

0.3970.528

0.5760.115

38.560.15

1745.21

63.350.90

1.1625.40

3.7640.283

0.2110.007

0.0790.057

20.010.08

1820.95

29.520.30

0.3968.50

0.4650.063

0.0330.021

0.0200.097

66.140.10

1918.62

26.080.38

0.4971.10

0.3130.092

0.0280.063

0.0070.054

70.070.06

2031.84

44.880.45

0.5849.84

1.0360.202

0.1450.143

0.1760.144

47.320.06

2137.10

52.280.53

0.6844.22

0.7240.086

0.0530.102

0.0840.096

41.290.08

2245.06

63.020.98

1.2626.76

2.6880.212

0.2310.013

0.0920.093

22.780.07

2345.87

64.290.90

1.1622.16

2.6851.010

0.3450.013

0.1810.218

17.260.44

2436.73

51.660.60

0.7745.46

0.5810.078

0.0340.038

0.0370.087

44.580.04

2540.61

57.630.30

0.3940.80

0.6710.103

0.0310.022

0.0270.103

30.940.06

2642.87

60.860.30

0.3936.38

0.5630.060

0.0280.026

0.0250.087

34.360.01

2741.31

58.630.30

0.3938.12

0.8470.136

0.0680.050

0.0620.067

36.470.02

2919.10

26.660.45

0.5868.36

2.0480.123

0.1390.014

0.0200.099

65.280.05

3044.37

63.010.30

0.3932.96

0.7460.035

0.0720.020

0.0190.131

31.720.12

3125.63

36.210.30

0.3961.50

0.6210.034

0.0580.007

0.0070.062

60.300.05

3245.94

65.150.37

0.4831.16

0.7080.026

0.0750.016

0.0220.117

30.020.01

3524.43

34.280.45

0.5863.00

0.6160.043

0.0340.010

0.0140.067

61.360.04

3641.06

58.270.30

0.3937.96

0.7180.051

0.0540.020

0.0280.118

35.740.13

3742.26

60.090.23

0.3036.48

0.6500.044

0.0350.014

0.0250.233

34.340.02

3844.37

63.120.22

0.2832.94

0.7680.074

0.0460.031

0.0360.077

31.300.02

Page 1 of 3

Sample N

umber

Fe

Hem

atiteF

e++F

eOSiO

2A

L2O

3C

aOM

gON

a2OK

2OM

nOF

reeSiO2

CO

2

3910.06

13.740.45

0.5884.82

0.3030.033

0.0210.003

0.0050.020

82.780.01

4028.93

40.830.37

0.4855.04

0.4760.075

0.0660.020

0.0210.068

54.240.03

4126.74

37.470.53

0.6859.14

0.4670.070

0.0380.036

0.0380.067

56.240.01

4224.93

35.000.45

0.5862.12

0.2270.044

0.0200.007

0.0090.035

61.520.03

4330.88

43.720.30

0.3951.82

0.4830.040

0.0480.010

0.0170.066

51.680.06

4430.73

43.290.45

0.5852.48

0.5110.020

0.0490.007

0.0120.076

51.440.02

4551.86

73.720.30

0.3919.40

2.0270.134

0.1410.017

0.0500.186

15.280.01

4653.21

75.650.30

0.3917.22

2.0260.134

0.1360.017

0.0440.183

13.700.03

4730.53

43.320.23

0.3052.92

0.5390.044

0.0430.030

0.0360.077

50.700.02

4834.44

48.810.30

0.3947.20

0.4970.061

0.0460.038

0.0490.082

46.960.03

4927.49

38.660.45

0.5857.22

0.3410.033

0.0380.006

0.0090.080

54.630.03

5028.69

40.470.38

0.4956.46

0.5480.089

0.0520.031

0.0340.088

54.640.05

5139.05

55.400.30

0.3939.72

0.2860.023

0.0330.004

0.0060.052

37.930.04

5224.73

34.930.30

0.3962.12

0.5820.084

0.0550.033

0.0470.065

60.520.08

5326.53

37.500.30

0.3958.94

0.4210.023

0.0480.021

0.0270.137

56.980.05

5426.44

37.260.38

0.4960.02

0.3930.038

0.0400.007

0.0110.052

58.660.03

5536.35

51.430.38

0.4943.10

0.4910.043

0.0570.010

0.0160.096

43.090.05

5638.43

54.410.37

0.4842.88

0.5720.057

0.0790.032

0.0470.106

40.660.03

5848.94

68.900.75

0.9726.12

0.3300.045

0.0540.004

0.0060.201

24.880.42

5728.33

39.860.45

0.5855.92

0.3980.030

0.0210.006

0.0110.041

55.180.01

5941.13

58.470.23

0.3036.90

0.4390.055

0.0720.013

0.0150.195

36.560.15

6051.66

73.430.30

0.3922.06

0.3790.032

0.0560.004

0.0080.194

21.200.14

7634.97

49.450.38

0.4946.30

0.4250.061

0.0710.013

0.0160.169

45.860.14

7731.48

44.360.45

0.5851.40

0.3850.071

0.0800.015

0.0170.137

49.200.06

7837.62

53.360.30

0.3942.48

0.4960.063

0.0590.019

0.0200.136

39.900.08

Page 2 of 3

Sample N

umber

Fe

Hem

atiteF

e++F

eOSiO

2A

L2O

3C

aOM

gON

a2OK

2OM

nOF

reeSiO2

CO

2

7925.38

35.740.38

0.4961.96

0.4430.035

0.0410.006

0.0090.051

61.180.01

8020.39

28.620.37

0.4867.76

0.3460.048

0.0340.005

0.0070.084

67.220.07

8119.55

27.520.30

0.3969.84

0.3670.065

0.0390.019

0.0200.068

69.060.06

8258.36

82.250.83

1.0712.32

0.3610.073

0.0880.003

0.0060.242

11.120.74

Page 3 of 3

stockpile ownership composition u

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